Estimating The Carbon Footprint Of Digital Agriculture Deployment: A Parametric Bottom-Up Modelling Approach

TL;DR

This paper introduces a bottom-up model to estimate the carbon footprint of digital agriculture, considering diverse device types and farm sizes, revealing complex environmental impacts of digital deployment.

Contribution

It presents a novel parametric approach that accounts for device heterogeneity and farm size distribution in assessing digital agriculture's environmental footprint.

Findings

Digital devices in agriculture have varied carbon footprints.

More complex devices often have higher footprints without performance benefits.

Farm size distribution influences overall digital agriculture emissions.

Abstract

Digitalization appears as a lever to enhance agriculture sustainability. However, existing works on digital agriculture's own sustainability remain scarce, disregarding the environmental effects of deploying digital devices on a large-scale. We propose a bottom-up method to estimate the carbon footprint of digital agriculture scenarios considering deployment of devices over a diversity of farm sizes. It is applied to two use-cases and demonstrates that digital agriculture encompasses a diversity of devices with heterogeneous carbon footprints and that more complex devices yield higher footprints not always compensated by better performances or scaling gains. By emphasizing the necessity of considering the multiplicity of devices, and the territorial distribution of farm sizes when modelling digital agriculture deployments, this study highlights the need for further exploration of the first-order effects of digital technologies in agriculture.